Studying the Relationship between Satellite-Derived Evapotranspiration and Crop Yield: A Case Study of the Cauvery River Basin

Satellite-derived evapotranspiration (ETa) products serve global applications, including drought monitoring and food security assessment. This study examines the applicability of ETa data from two distinct sources, aiming to analyze its correlation with crop yield (rice, maize, barley, soybean). Given the critical role of crop yield in economic and food security contexts, monthly and yearly satellite-derived ETa data were assessed for decision-makers, particularly in drought-prone and food-insecure regions. Utilizing QGIS, zonal statistics operations and time series graphs were employed to compare ETa with crop yield and ET anomaly. Data processing involved converting NRSC daily data to monthly and extracting single-pixel ET data using R Studio. Results reveal USGSFEWS as a more reliable ETa source, offering better accuracy and data continuity, especially during monsoon seasons. However, the correlation between crop yield and ETa ranged from 12% to 35%, while with ET anomaly, it ranged from 35% to 55%. Enhanced collection of satellite-based ETa and crop-yield data is imperative for informed decision-making in these regions. Despite limitations, ETa can moderately guide decisions regarding crop-yield management.

Authors

Institutions

Publication Details

Journal
AgriEngineering
Published
2024-08-05
DOI
https://doi.org/10.3390/agriengineering6030154
Citations
3
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.85

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Studying the Relationship between Satellite-Derived Evapotranspiration and Crop Yield: A Case Study of the Cauvery River Basin

Venkata Reddy Keesara, A Anand, Venkataramana Sridhar
3 citations
AgriEngineering
Plant Water Relations and Carbon Dynamics
0.85
article

Studying the Relationship between Satellite-Derived Evapotranspiration and Crop Yield: A Case Study of the Cauvery River Basin

Venkata Reddy Keesara, A Anand, Venkataramana Sridhar
article en
3 citations

Abstract

Satellite-derived evapotranspiration (ETa) products serve global applications, including drought monitoring and food security assessment. This study examines the applicability of ETa data from two distinct sources, aiming to analyze its correlation with crop yield (rice, maize, barley, soybean). Given the critical role of crop yield in economic and food security contexts, monthly and yearly satellite-derived ETa data were assessed for decision-makers, particularly in drought-prone and food-insecure regions. Utilizing QGIS, zonal statistics operations and time series graphs were employed to compare ETa with crop yield and ET anomaly. Data processing involved converting NRSC daily data to monthly and extracting single-pixel ET data using R Studio. Results reveal USGSFEWS as a more reliable ETa source, offering better accuracy and data continuity, especially during monsoon seasons. However, the correlation between crop yield and ETa ranged from 12% to 35%, while with ET anomaly, it ranged from 35% to 55%. Enhanced collection of satellite-based ETa and crop-yield data is imperative for informed decision-making in these regions. Despite limitations, ETa can moderately guide decisions regarding crop-yield management.

AgriEngineeringVol. 6(3)
National Institute of Technology Warangal (IN), Virginia Tech (US)
U.S. Department of Agriculture, United States - India Educational Foundation, National Institute of Food and Agriculture
Zero hunger
Openalex Percentile: Top 28%
Plant Water Relations and Carbon Dynamics
0.85
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.